I want to clarify something. Reranker is a general term that can refer to any model used for reranking. It is independent of implementation.

What you refer to

because reranker models look at the two pieces of content simultaneously and can be fine tuned to the domain in question. They shouldn't be used for the initial retrieval because the evaluation time is O(n²) as each combination of input

Is a specific implementation known as CrossEncoder that is common for reranking models but not retrieval ones for the reasons you described. But you can also use any other architecture